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A Technique for Hand Gesture Recognition on Real Time Basis

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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2018
Authors:
Ayushi Shrivastav, Radhika Agrawal, S. G. Mundada
10.5120/ijca2018917613

Ayushi Shrivastav, Radhika Agrawal and S G Mundada. A Technique for Hand Gesture Recognition on Real Time Basis. International Journal of Computer Applications 181(9):43-46, August 2018. BibTeX

@article{10.5120/ijca2018917613,
	author = {Ayushi Shrivastav and Radhika Agrawal and S. G. Mundada},
	title = {A Technique for Hand Gesture Recognition on Real Time Basis},
	journal = {International Journal of Computer Applications},
	issue_date = {August 2018},
	volume = {181},
	number = {9},
	month = {Aug},
	year = {2018},
	issn = {0975-8887},
	pages = {43-46},
	numpages = {4},
	url = {http://www.ijcaonline.org/archives/volume181/number9/29803-2018917613},
	doi = {10.5120/ijca2018917613},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}
}

Abstract

Sign gesture is a non-verbal visual language, different from the spoken language in terms of medium of communication, but serves the same function for hearing & speech impaired community. Gesture Recognition, and more specifically hand gesture recognition, is one of the typical methods used in sign language for non-verbal communication. It is often very difficult for the hearing & speech impaired community to communicate their ideas and creativity to the normal humans. This paper focuses on discussing different methods to identify the gesture. Method for hand segmentation is discussed in terms of the different approaches to sub-components of the identifying the gesture. The judgement parameters are accuracy in real time performance, processing time, processor utilization, etc.

References

  1. M. Panwar (Centre for Development of Advanced Computing, Noida), ‘Hand Gesture Recognition based on Shape Parameters’
  2. Y. Fang et. al. 2007, ‘A REAL-TIME HAND GESTURE RECOGNITION METHOD’
  3. T. Nguyen & H. Huynh, ‘Static Hand Gesture Recognition Using Artificial Neural Network’, Journal of Image and Graphics, Volume 1, No.1, March, 2013
  4. M. Quraishi et. al., ‘A Novel Human Hand Finger Gesture Recognition U sing Machine Learning’, 2012 2nd IEEE International Conference on Parallel, Distributed and Grid Computing
  5. S. Oniga & I. Orha, ‘Intelligent Human-Machine Interface Using Hand Gestures Recognition’
  6. L. Chen et. al., ‘A Survey on Hand Gesture Recognition’, 2013 International Conference on Computer Sciences and Applications
  7. M.Murugeswari (PG Scholar, Communication Systems, Anna University,Tamil Nadu) ,S.Veluchamy (Assistant Professor, Communication Systems, Anna University,Tamil Nadu), ‘Hand Gesture Recognition system for Real-Time Application’, 2014 IEEE International Conference on Advanced Communication Control and Computing Technologies (ICACCCT)
  8. M. Tao & L. Ma, ‘A Hand Gesture Recognition Model Based on Semi-supervised Learning’, 2015 7th International Conference on Intelligent Human-Machine Systems and Cybernetics
  9. R. Agrawal & N. Gupta, ‘Real Time Hand Gesture Recognition for Human Computer Interaction’, 2016 IEEE 6th International Conference on Advanced Computing
  10. Sourav Bhowmick et. al, ‘Hand Gesture Recognition of English Alphabets using Artificial Neural Network’, 2015 IEEE 2nd International Conference on Recent Trends in Information Systems (ReTIS)
  11. S. Gawande & Prof. N. Chopde, ‘Neural Network based Hand Gesture Recognition’, International Journal of Emerging Research in Management &Technology ISSN:2278-9359 (Volume-2, Issue-3)

Keywords

Hand gesture recognition, Image processing, Human computer interaction (HCI), K-means clustering, Hand segmentation, hand gestures